Feature Importance Stability

Feature Importance Stability is a measurement construct that quantifies the consistency of feature importance rankings across varying models, datasets, or perturbations, thereby distinguishing itself from general feature selection methods by emphasizing reliability and reproducibility of feature relevance assessments.

9

Publications

578

Citations

31

Authors

17

Institutions

Publications per year

2017–2026

8

Authors

31

  1. CS
    Clemens Stachl

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 72 citations

    2

    h-index

  2. BB
    Bernd Bischl

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 72 citations

    2

    h-index

  3. JH
    Julia Herbinger

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 72 citations

    2

    h-index

  4. GC
    Giuseppe Casalicchio

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 72 citations

    2

    h-index

  5. QA
    Quay Au

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 72 citations

    2

    h-index

1–5 of 31

Venues

  1. arXiv (Cornell University)

    Repository · 1 publications · 10 citations

    1

    h-index

  2. Hydrology and earth system sciences

    1 publications · 22 citations

    1

    h-index

  3. Journal of Hazardous Materials

    1 publications · 114 citations

    1

    h-index

  4. IEEE Geoscience and Remote Sensing Letters

    GRSL · 1 publications · 134 citations

    1

    h-index

  5. Information Sciences

    1 publications · 35 citations

    1

    h-index

1–5